AURA: Amplifying Understanding, Resilience, and Awareness for Responsible AI Content Work

Behind the scenes of maintaining the safety of technology products from harmful and illegal digital content lies unrecognized human labor. The recent rise in the use of generative AI technologies and the accelerating demands to meet responsible AI (RAI) aims necessitates an increased focus on the labor behind such efforts in the age of AI. This study investigates the nature and challenges of content work that supports RAI efforts, or "RAI content work," that spans content moderation, data labeling, and red teaming -- through the lived experiences of content workers. We conduct a formative survey and semi-structured interview studies to develop a conceptualization of RAI content work and a subsequent framework of recommendations for providing holistic support for content workers. We validate our recommendations through a series of workshops with content workers and derive considerations for and examples of implementing such recommendations. We discuss how our framework may guide future innovation to support the well-being and professional development of the RAI content workforce.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-05-02
DOI
https://doi.org/10.1145/3710931
Citations
3
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
7.44
Controls
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article

AURA: Amplifying Understanding, Resilience, and Awareness for Responsible AI Content Work

Mary Czerwinski, Judith Amores Fernandez, Mary L. Gray, Jina Suh et al.
3 citations
Proceedings of the ACM on Human-Computer Interaction
Hate Speech and Cyberbullying Detection
7.44
article

AURA: Amplifying Understanding, Resilience, and Awareness for Responsible AI Content Work

Mary Czerwinski, Judith Amores Fernandez, Mary L. Gray, Jina Suh, Alice Qian Zhang, Hong Shen
article en
3 citations

Abstract

Behind the scenes of maintaining the safety of technology products from harmful and illegal digital content lies unrecognized human labor. The recent rise in the use of generative AI technologies and the accelerating demands to meet responsible AI (RAI) aims necessitates an increased focus on the labor behind such efforts in the age of AI. This study investigates the nature and challenges of content work that supports RAI efforts, or "RAI content work," that spans content moderation, data labeling, and red teaming -- through the lived experiences of content workers. We conduct a formative survey and semi-structured interview studies to develop a conceptualization of RAI content work and a subsequent framework of recommendations for providing holistic support for content workers. We validate our recommendations through a series of workshops with content workers and derive considerations for and examples of implementing such recommendations. We discuss how our framework may guide future innovation to support the well-being and professional development of the RAI content workforce.

Proceedings of the ACM on Human-Computer InteractionVol. 9(2)
Microsoft (United States) (US), Carnegie Mellon University (US)
Decent work and economic growth
Openalex Percentile: Top 3%
Hate Speech and Cyberbullying Detection
7.44
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